Comparison of cue-locked and feedback-locked decoding. by Sam Hall-McMaster (10343795)

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COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. COMET leverages carefully curated data sets encompassing 2685 human targets of therapeutic relevance and 990,944 ligand-target interaction pairs. …”

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. COMET leverages carefully curated data sets encompassing 2685 human targets of therapeutic relevance and 990,944 ligand-target interaction pairs. …”

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. COMET leverages carefully curated data sets encompassing 2685 human targets of therapeutic relevance and 990,944 ligand-target interaction pairs. …”

The list of parameters of the modified data set for machine learning (<i>n</i> = 162). by Uğur Ejder (22683228)

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Data Sheet 1_IGSA-SAC: a novel approach for intrusion detection using improved gravitational search algorithm and soft actor-critic.docx by Lizhong Jin (20991293)

SCADET algorithm parameter configuration (Python implementation). by Xiaolong Zhang (470454)

Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

“…These classification algorithms often requires conversion of a medical data to another space in which the original data is reduced to important values or moments. …”

Data and code resources. by Sam Hall-McMaster (10343795)

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Extracting Residue Solvent Exposure from Covalent Labeling Data with Machine Learning: A Hybrid Approach for Protein Structure Prediction by Elijah H. Day (21396836)

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The structure diagram of the BS-CP algorithm. by Jiaqi Liu (309587)

“…We first present the BS-CP1 algorithm, which is an efficient implementation using assumed density filtering (ADF). …”

Comparison of performance between the machine learning pipelines for tissue classification. by Ashutosh P. Raman (19825936)

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Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%). by Uğur Ejder (22683228)

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The machine learning framework implemented in the present work. by Akshansh Mishra (21001499)

PATH (with persistence fingerprint) runs significantly faster than TNet-BP, a representative binding affinity prediction algorithm that uses persistent homology, on larger protein-... by Yuxi Long (11024307)

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Comparison of city decoders trained on session one and session two data. by Sam Hall-McMaster (10343795)

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pdig.0000602.t003 - Machine learning approaches in non-contact autofluorescence spectrum classification by Ashutosh P. Raman (19825936)

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Table 1_Leveraging data augmentation for machine learning models in predicting depression and anxiety using the Revised Child Anxiety and Depression Scale clinical reports.docx by Saleha Noor (22697930)

“…</p>Conclusion<p>The findings suggest that the Random Forest algorithm using 46 features suits the data well and has the potential to be further developed as a decision support system for the concerned professionals and improve the usual way of screening anxiety and depression in children and adolescents.…”

Table 2_Leveraging data augmentation for machine learning models in predicting depression and anxiety using the Revised Child Anxiety and Depression Scale clinical reports.docx by Saleha Noor (22697930)

“…</p>Conclusion<p>The findings suggest that the Random Forest algorithm using 46 features suits the data well and has the potential to be further developed as a decision support system for the concerned professionals and improve the usual way of screening anxiety and depression in children and adolescents.…”

Data Sheet 1_Construction of a prognostic model for endometrial cancer related to programmed cell death using WGCNA and machine learning algorithms.zip by Weicheng Pan (12629762)